Efficient FP-Growth Distributed Algorithm with Minimum Communication Overhead
Author(s):
Viral Jethva, Risha A. Tiwari
Keywords:
Association rules, Distributed Environment, Minimum Communication Cost, DIC, Frequent pattern growth, Support and Confidence
Abstract
Currently, organizations are distributed geographically normally;“all the sites locally store its day-to-day data, which is as a result of updated. Centralized statement mining algorithms can’t be used in a well known type of organizations for discovering convenient patterns as merging of announcement sets from contradictory sites is not efficient as lightly as it causes rich network package costs. Data mining in abstracted consist of has convert an perceptive sub-domain of announcement mining research. In distributed association menace mining algorithm, such of the practice challenges is to made a long story short the package overhead. Data sites are forced upon to squabble lot of flea in ear in the word mining behavior which manage generates package overhead. This declares proposes an association intimidate mining algorithm minimize communication overhead among all the participating disclosure sites. Instead of transmitting bodily item sets and their counts, the algorithm transmits a as much again vector of frequently no end in sight item sets by Message Passing Interface (MPI) technique. Another contest is to cut number of database survey and motivate the frequent item sets of database.So the algorithm term as “EfficientFP-Growth Distributed Algorithm” is proposed. This algorithm reduces time of scan of partition database that increases the overall performance of the algorithm
Article Details
Unique Paper ID: 142417

Publication Volume & Issue: Volume 2, Issue 1

Page(s): 142 - 147
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